But in reality, new products/inventions, even improvements on existing ones, are usually not that simple. They add an extra dimension, more freedom to find better solutions to problems. But in a high-level, low dimensional description, this freedom can be collapsed into a change in parameters, or really added as extra dimension, if the effects are important enough.
Funny thing is, I am currently working on shape optimization, where it is completely natural to change the number of parameters used to describe the shape, and thus the dimension of the problem.
A related field is order reduction, where you try to (locally) approximate a physical phenomenon by its most important modes. If there is a change in the physics, you can either modify the modes, but keep the same number of them, or you might find that for the new situation more modes are required to describe it well enough.
I would suggest this is a good analogy for your innovation/improvement distinction
I am familiar with dimension reduction (proper orthogonal modes, principal componets, factor analysis...) and you're right, at some level the number of variables is a matter of choice. But you still have to be able to close the system of equations. You can always ascribe the effect of all the neglected modes to "noise", though. We have met the enemy, and he is us — Pogo
